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Development of Korean Male Body Model for Computational Dosimetry
이애경,최우영,정민석,최형도,최재익 한국전자통신연구원 2006 ETRI Journal Vol.28 No.1
The dimensions of the human body vary by age, sex, and race. The internal structure and outer dimensions of a body exposed to an electromagnetic field is important for accurate dosimetry. The average physical size of Korean adult males between the ages 18 to 24 was investigated, and a male volunteer was selected whose physical condition is within the physical standards, ± 5%. Magnetic resonance images and partially computerized tomography images of the volunteer were acquired. The intervals between the transverse images were 1 mm for the head and 3 mm for the rest of the body. About 30 different tissues were manually classified by an anatomist on the raw images, and the segmented images were implemented in the form of a text file appropriate for numerical formulation.
[자유기고문]성인과 어린이: 휴대전화 사용에 대한 건강영향에 차이가 있는가?
이애경,최형도,최재익 한국전자파학회 2004 전자파기술 Vol.15 No.4
본 고는 최근 이슈가 되고 있는 어린이의 휴대전화 사용에 대해, 휴대전화기에서 복사되는 전자파 에너지가 성인과 달리 작용할 가능성이 있는지에 관한 연구 또는 보고 자료를 수집하여 다양한 각도에서 조사한 것이다. 공학적 관점에서 휴대전화 사용에 있어 어린이와 성인의 전자파 흡수율에 차이를 가져올 수 있는가에 관한 연구 결과를 기술하고 있으며, 각각 형태적 측면에서 성인과 어린이를 나타내는 각기 다른 크기의 머리 형태에서 전자파 흡수율의 차이가 있는지와 생체의 재료(재질) 측면에서 연령층에 따라 조직의 전기적 특성에 변화를 알아보았다. 그 다음 휴대전화기에 가장 가까이 위치하는 인체 머리의 성장 과정상의 변화를 살펴봄으로써 생물학적 측면에서 어린이가 성인에 비해 취약할 가능성이 있는지 검토하였다. 그러나 이러한 가능성을 현재로서는 명확히 판단하기 어려우며, 원인 규명을 위한 추가 연구 및 다양한 연구 분야간 협력이 요구됨을 알 수 있었다.<br/>
이애경,박일수,강성홍,강현철 한국보건행정학회 2006 보건행정학회지 Vol.16 No.2
As prior studies indicate that chronic diseases are mainly attributed to health behavior, preventive health care rather than treatment for illness needs to improve health status. Since chronic conditions require long-term therapy, health care expenditures to treat chronic diseases have been substantial burden at national level. In this point of view, this study suggests that the health promotion program should be based on Knowledge Based System. Using Data Mining Technique, we developed a predictive model for preventive healthcare management on diabetes mellitus. Generally, in the outbreak of diabetes mellitus there is a difference in lifestyle and the risk factors according to gender. So we developed a predictive model in accordance with gender difference and applied the Logistic Regression Model based on Data Mining process. The results of the study were as follow. The lift of the last predictive model was an average 2.23 times(male model : 2.13, female model 2.33) more improved than in the random model in upper 10% group. The health risk factors of diabetes mellitus are gender, age, a place of residence, blood pressure, glucose, smoking, drinking, exercise rate. On the basis of these factors, we suggest the program of the health promotion.
이애경 한국카운슬러협회 2009 相談과 指導 Vol.44 No.-
인지행동치료(cognitive-behavioral therapy)'라는 용어는 1970년대 중반에 처음으로 문헌에 사용되었다. 그리고 그 효과에 대한 통제된 연구는 70년대 후반에서야 발표되었다. 그 이후 짧은 기간이 흘렀을 뿐인데도 인지행동치료는 유럽 및 북미를 비롯한 전 세계에 널리 보급되었다. 인지행동치료를 적용하는 치료자들의 수가 점차 늘어나면서 현재 세계 여러 나라에서 임상연구와 실제에서 주로 많이 사용되는 심리치료접근법이 되었다. 우리나라에서도 임상장면 곳곳에서 인지행동치료가 시행되고 있고 임상심리학자, 정신과의사를 비롯한 정신보건 전문가들의 '한국인지행동치료연구회', 임상심리학회의 '인지행동치료연구회' 등의 학회들이 생겨났다.
이애경,이선미,박일수 한국보건행정학회 2006 보건행정학회지 Vol.16 No.1
This study was conducted as the primary work to develop a customer relationship management (CRM) system to improve the performance of health screening programs. The specific aims of the study was to identify and classify the characteristics of the people who did not receive their health screening using decision trees and to propose management strategies according to their characteristics identified. The data on a total of 5,102,761 subjects of health screening provided by the National Health Insurance Program in the year of 2002 were used. The target variable was whether they underwent their health screening. The input variables included a total of 27. The SAS 9.1 version was used for data preprocessing and statistical analyses. SAS Enterprise Miner was used to develop the decision trees model. The decision trees identified the factors greatly affecting the health screening. In the non-disease group, the highest rate of non-examinees was characterized by: no experience of receiving a health screen, household’s age, non-insured episode for the last one year, and patients’ age. In the disease group, the one showing the highest rate of non-examinees was characterized by: no experience of receiving a health screening, no experience of going to public health center or midwife clinic for the last one year, and examinees’ age. Developing CRM systems for health screening management taking into account the individual characteristics would be considerably helpful to increase the rate of receiving health screening.